Overview

Dataset statistics

Number of variables45
Number of observations6771
Missing cells96
Missing cells (%)< 0.1%
Duplicate rows191
Duplicate rows (%)2.8%
Total size in memory2.3 MiB
Average record size in memory360.0 B

Variable types

CAT33
NUM10
BOOL2

Warnings

emd_lable has constant value "6771" Constant
emd_lable2 has constant value "6771" Constant
Dataset has 191 (2.8%) duplicate rows Duplicates
pax_name has a high cardinality: 6489 distinct values High cardinality
pax_passport has a high cardinality: 6447 distinct values High cardinality
pref_line_y3_1 has a high cardinality: 144 distinct values High cardinality
pref_line_y3_2 has a high cardinality: 156 distinct values High cardinality
pref_line_y3_3 has a high cardinality: 175 distinct values High cardinality
pref_line_y3_4 has a high cardinality: 147 distinct values High cardinality
pref_line_y3_5 has a high cardinality: 147 distinct values High cardinality
pref_city_y3_2 has a high cardinality: 83 distinct values High cardinality
pref_city_y3_3 has a high cardinality: 88 distinct values High cardinality
flt_cnt_y3 has a high cardinality: 91 distinct values High cardinality
avg_dist_cnt_y3 is highly correlated with avg_dist_cnt_y2High correlation
avg_dist_cnt_y2 is highly correlated with avg_dist_cnt_y3High correlation
tkt_avg_amt_y3 is highly correlated with tkt_avg_amt_y2High correlation
tkt_avg_amt_y2 is highly correlated with tkt_avg_amt_y3High correlation
seg_flight is highly correlated with seg_route_toHigh correlation
seg_route_to is highly correlated with seg_flightHigh correlation
pit_add_chnl_y3 has 96 (1.4%) missing values Missing
seat_window_cnt_y3 is highly skewed (γ1 = 25.06414781) Skewed
pax_name is uniformly distributed Uniform
pax_passport is uniformly distributed Uniform
seat_walkway_cnt_y3 has 6129 (90.5%) zeros Zeros
seat_window_cnt_y3 has 6289 (92.9%) zeros Zeros
seat_middle_cnt_y3 has 6353 (93.8%) zeros Zeros
avg_dist_cnt_y2 has 6084 (89.9%) zeros Zeros
avg_dist_cnt_y3 has 6086 (89.9%) zeros Zeros
flt_leg_i_cnt_y3 has 6004 (88.7%) zeros Zeros
mdl_mcv has 6103 (90.1%) zeros Zeros
tkt_avg_amt_y1 has 6266 (92.5%) zeros Zeros
tkt_avg_amt_y2 has 6128 (90.5%) zeros Zeros
tkt_avg_amt_y3 has 6102 (90.1%) zeros Zeros

Reproduction

Analysis started2021-03-11 15:50:35.600437
Analysis finished2021-03-11 15:51:09.173269
Duration33.57 seconds
Software versionpandas-profiling v2.9.0
Download configurationconfig.yaml

Variables

pax_name
Categorical

HIGH CARDINALITY
UNIFORM

Distinct6489
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
884e2983a0740b728adb5aa8be5d5837
 
5
6e32e5d6e1649f0c73bcc509b5c8e3b9
 
4
dc81215b4e423a7eae9bbc85bc4ae95b
 
4
7623c905c7b5f3155e67e1647008c985
 
4
f1472740493d0096a47c88dd497fb18b
 
3
Other values (6484)
6751 
ValueCountFrequency (%) 
884e2983a0740b728adb5aa8be5d583750.1%
 
6e32e5d6e1649f0c73bcc509b5c8e3b940.1%
 
dc81215b4e423a7eae9bbc85bc4ae95b40.1%
 
7623c905c7b5f3155e67e1647008c98540.1%
 
f1472740493d0096a47c88dd497fb18b3< 0.1%
 
e3133705b3ab483acb909361197e66e83< 0.1%
 
ecd4cc8f063a1ad4d64ce5db74e84e8c3< 0.1%
 
d933b7ab2b0b2587eba24c5bb9da5ff73< 0.1%
 
fc4e5102e5da3d80649ac88dd3ef16263< 0.1%
 
779999ae7a2cf515220842c0d27ca4d93< 0.1%
 
Other values (6479)673699.5%
 
2021-03-11T23:51:09.354293image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6236 ?
Unique (%)92.1%
2021-03-11T23:51:09.553378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length32
Mean length32
Min length32

pax_passport
Categorical

HIGH CARDINALITY
UNIFORM

Distinct6447
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0cf357779a8597a092bdb7e8c4dd0fb9
 
5
04706e7ca865da4e565d92593968add9
 
5
a64fed95293b981720bb553074f2fc06
 
5
eb2cb640b74cf4ff8354d97832969515
 
4
5fcafded7a9ecb863973769193664b22
 
4
Other values (6442)
6748 
ValueCountFrequency (%) 
0cf357779a8597a092bdb7e8c4dd0fb950.1%
 
04706e7ca865da4e565d92593968add950.1%
 
a64fed95293b981720bb553074f2fc0650.1%
 
eb2cb640b74cf4ff8354d9783296951540.1%
 
5fcafded7a9ecb863973769193664b2240.1%
 
eba97d2a193f832add8c2db9aa23a82f3< 0.1%
 
ee5657503f9828f74bb82e1aeb820b543< 0.1%
 
d1f777e74758cb7bbaf362c74bfbc9da3< 0.1%
 
dbe116c4a1eb51b0c6cb14e9f62a11e53< 0.1%
 
fd709cf0b693eb678b6f22b53f64eea83< 0.1%
 
Other values (6437)673399.4%
 
2021-03-11T23:51:09.697378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6165 ?
Unique (%)91.1%
2021-03-11T23:51:09.824403image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length32
Median length32
Mean length32
Min length32

seg_route_to
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
LAX
3493 
JFK
3278 
ValueCountFrequency (%) 
LAX349351.6%
 
JFK327848.4%
 
2021-03-11T23:51:09.920375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-03-11T23:51:09.983375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:10.054375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length3
Mean length3
Min length3

seg_flight
Categorical

HIGH CORRELATION

Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
AB1008
2028 
AB1006
1925 
AB1009
1440 
AB1010
1353 
AB1015
 
25
ValueCountFrequency (%) 
AB1008202830.0%
 
AB1006192528.4%
 
AB1009144021.3%
 
AB1010135320.0%
 
AB1015250.4%
 
2021-03-11T23:51:10.164378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-03-11T23:51:10.243378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:10.335375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length6
Median length6
Mean length6
Min length6

seg_cabin
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
Y
5845 
J
925 
F
 
1
ValueCountFrequency (%) 
Y584586.3%
 
J92513.7%
 
F1< 0.1%
 
2021-03-11T23:51:10.444379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2021-03-11T23:51:10.518379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:10.591378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

emd_lable
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6771 
ValueCountFrequency (%) 
06771100.0%
 
2021-03-11T23:51:10.657379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

emd_lable2
Boolean

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6771 
ValueCountFrequency (%) 
06771100.0%
 
2021-03-11T23:51:10.686378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

gender
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6401 
M
 
188
F
 
176
U
 
6
ValueCountFrequency (%) 
0640194.5%
 
M1882.8%
 
F1762.6%
 
U60.1%
 
2021-03-11T23:51:10.753379image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-03-11T23:51:10.823375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:10.908375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length1
Median length1
Mean length1
Min length1

age
Categorical

Distinct13
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6441 
21-30
 
77
31-40
 
74
60+
 
64
51-60
 
62
Other values (8)
 
53
ValueCountFrequency (%) 
0644195.1%
 
21-30771.1%
 
31-40741.1%
 
60+640.9%
 
51-60620.9%
 
41-50450.7%
 
11朿0旿2002/2/102< 0.1%
 
11朿0旿2002/3/211< 0.1%
 
0-101< 0.1%
 
11朿0旿2008/5/301< 0.1%
 
Other values (3)3< 0.1%
 
2021-03-11T23:51:11.018697image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique6 ?
Unique (%)0.1%
2021-03-11T23:51:11.133696image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length15
Median length1
Mean length1.185349284
Min length1
Distinct5
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6418 
中国
 
341
美国
 
10
新加坿0
 
1
加拿夿0
 
1
ValueCountFrequency (%) 
0641894.8%
 
中国3415.0%
 
美国100.1%
 
新加坿01< 0.1%
 
加拿夿01< 0.1%
 
2021-03-11T23:51:11.246696image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2021-03-11T23:51:11.323699image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:11.414699image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length1
Mean length1.052724856
Min length1

nation_name
Categorical

Distinct21
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6480 
美国
 
157
中国
 
95
韩国
 
6
菲律宿0
 
4
Other values (16)
 
29
ValueCountFrequency (%) 
0648095.7%
 
美国1572.3%
 
中国951.4%
 
韩国60.1%
 
菲律宿040.1%
 
中国台湾40.1%
 
新加坿040.1%
 
泰国3< 0.1%
 
墨西哿03< 0.1%
 
马来西亚2< 0.1%
 
Other values (11)130.2%
 
2021-03-11T23:51:11.541223image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique9 ?
Unique (%)0.1%
2021-03-11T23:51:11.661095image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length1
Mean length1.051247969
Min length1

province_name
Categorical

Distinct28
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6677 
SH
 
31
JS
 
11
ZJ
 
7
AH
 
7
Other values (23)
 
38
ValueCountFrequency (%) 
0667798.6%
 
SH310.5%
 
JS110.2%
 
ZJ70.1%
 
AH70.1%
 
NY50.1%
 
U3< 0.1%
 
S3< 0.1%
 
BJ3< 0.1%
 
HA2< 0.1%
 
Other values (18)220.3%
 
2021-03-11T23:51:11.791144image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique14 ?
Unique (%)0.2%
2021-03-11T23:51:12.099748image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length12
Median length1
Mean length1.02230099
Min length1

member_level
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6495 
STD
 
237
SILHL
 
15
GOLHL
 
12
PLTSL
 
10
ValueCountFrequency (%) 
0649595.9%
 
STD2373.5%
 
SILHL150.2%
 
GOLHL120.2%
 
PLTSL100.1%
 
网站2< 0.1%
 
2021-03-11T23:51:12.223377image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-03-11T23:51:12.311375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:12.424375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length1
Mean length1.092157732
Min length1

enroll_chnl
Categorical

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6497 
网站
 
223
销售单使0
 
16
手机平台
 
16
其它
 
8
Other values (2)
 
11
ValueCountFrequency (%) 
0649796.0%
 
网站2233.3%
 
销售单使0160.2%
 
手机平台160.2%
 
其它80.1%
 
电话60.1%
 
移动客舱50.1%
 
2021-03-11T23:51:12.544378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-03-11T23:51:12.619378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:12.725378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length5
Median length1
Mean length1.053758677
Min length1
Distinct15
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6519 
773
 
185
33L
 
14
320
 
9
73E
 
8
Other values (10)
 
36
ValueCountFrequency (%) 
0651996.3%
 
7731852.7%
 
33L140.2%
 
32090.1%
 
73E80.1%
 
73H70.1%
 
33E60.1%
 
33H50.1%
 
73840.1%
 
73L40.1%
 
Other values (5)100.1%
 
2021-03-11T23:51:12.848375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2021-03-11T23:51:12.973375image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.074435091
Min length1
Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6522 
773
 
86
33L
 
22
325
 
17
73E
 
15
Other values (15)
 
109
ValueCountFrequency (%) 
0652296.3%
 
773861.3%
 
33L220.3%
 
325170.3%
 
73E150.2%
 
738130.2%
 
33E120.2%
 
320120.2%
 
323110.2%
 
73H90.1%
 
Other values (10)520.8%
 
2021-03-11T23:51:13.105376image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-03-11T23:51:13.223378image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.073548959
Min length1
Distinct21
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
5924 
773
634 
320
 
38
73H
 
33
325
 
23
Other values (16)
 
119
ValueCountFrequency (%) 
0592487.5%
 
7736349.4%
 
320380.6%
 
73H330.5%
 
325230.3%
 
33L190.3%
 
33E180.3%
 
73E150.2%
 
333150.2%
 
33H110.2%
 
Other values (11)410.6%
 
2021-03-11T23:51:13.349380image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique2 ?
Unique (%)< 0.1%
2021-03-11T23:51:13.467441image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.250184611
Min length1
Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
5932 
773
 
223
325
 
113
73H
 
91
320
 
82
Other values (19)
 
330
ValueCountFrequency (%) 
0593287.6%
 
7732233.3%
 
3251131.7%
 
73H911.3%
 
320821.2%
 
33E510.8%
 
33L470.7%
 
73E350.5%
 
333340.5%
 
33H300.4%
 
Other values (14)1332.0%
 
2021-03-11T23:51:13.592588image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique1 ?
Unique (%)< 0.1%
2021-03-11T23:51:13.703633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.247821592
Min length1
Distinct25
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6130 
773
 
167
73H
 
57
320
 
55
325
 
52
Other values (20)
 
310
ValueCountFrequency (%) 
0613090.5%
 
7731672.5%
 
73H570.8%
 
320550.8%
 
325520.8%
 
73E380.6%
 
738360.5%
 
321320.5%
 
33E300.4%
 
33L270.4%
 
Other values (15)1472.2%
 
2021-03-11T23:51:13.828633image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2021-03-11T23:51:13.943596image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.189336878
Min length1
Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6331 
773
 
156
325
 
37
320
 
32
73E
 
28
Other values (18)
 
187
ValueCountFrequency (%) 
0633193.5%
 
7731562.3%
 
325370.5%
 
320320.5%
 
73E280.4%
 
73H270.4%
 
738210.3%
 
33H180.3%
 
33E180.3%
 
33L170.3%
 
Other values (13)861.3%
 
2021-03-11T23:51:14.064118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique3 ?
Unique (%)< 0.1%
2021-03-11T23:51:14.179115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.129966032
Min length1
Distinct28
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6452 
773
 
137
325
 
23
320
 
16
33E
 
13
Other values (23)
 
130
ValueCountFrequency (%) 
0645295.3%
 
7731372.0%
 
325230.3%
 
320160.2%
 
33E130.2%
 
323120.2%
 
333110.2%
 
33H110.2%
 
73H110.2%
 
33L100.1%
 
Other values (18)751.1%
 
2021-03-11T23:51:14.301115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique4 ?
Unique (%)0.1%
2021-03-11T23:51:14.415118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.090680845
Min length1

pref_line_y3_1
Categorical

HIGH CARDINALITY

Distinct144
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6040 
JFK-PVG
 
165
LAX-PVG
 
112
PVG-JFK
 
58
PVG-LAX
 
49
Other values (139)
 
347
ValueCountFrequency (%) 
0604089.2%
 
JFK-PVG1652.4%
 
LAX-PVG1121.7%
 
PVG-JFK580.9%
 
PVG-LAX490.7%
 
PVG-BKK250.4%
 
SIN-PVG250.4%
 
PVG-ICN190.3%
 
SFO-PVG130.2%
 
PVG-WNZ100.1%
 
Other values (134)2553.8%
 
2021-03-11T23:51:14.552119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique73 ?
Unique (%)1.1%
2021-03-11T23:51:14.676138image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length1
Mean length1.647762517
Min length1

pref_line_y3_2
Categorical

HIGH CARDINALITY

Distinct156
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6048 
PVG-JFK
 
132
JFK-PVG
 
91
PVG-LAX
 
85
LAX-PVG
 
83
Other values (151)
 
332
ValueCountFrequency (%) 
0604889.3%
 
PVG-JFK1321.9%
 
JFK-PVG911.3%
 
PVG-LAX851.3%
 
LAX-PVG831.2%
 
BKK-PVG160.2%
 
PVG-SFO110.2%
 
PVG-HKG100.1%
 
PVG-BKK90.1%
 
PVG-ORD70.1%
 
Other values (146)2794.1%
 
2021-03-11T23:51:14.809119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique78 ?
Unique (%)1.2%
2021-03-11T23:51:14.934118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length1
Mean length1.64067346
Min length1

pref_line_y3_3
Categorical

HIGH CARDINALITY

Distinct175
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6205 
PVG-LAX
 
73
PVG-JFK
 
58
JFK-PVG
 
42
LAX-PVG
 
33
Other values (170)
 
360
ValueCountFrequency (%) 
0620591.6%
 
PVG-LAX731.1%
 
PVG-JFK580.9%
 
JFK-PVG420.6%
 
LAX-PVG330.5%
 
PVG-HKG90.1%
 
PVG-BKK90.1%
 
SIN-PVG80.1%
 
WNZ-PVG80.1%
 
CAN-PVG70.1%
 
Other values (165)3194.7%
 
2021-03-11T23:51:15.065119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique84 ?
Unique (%)1.2%
2021-03-11T23:51:15.190118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length1
Mean length1.501550731
Min length1

pref_line_y3_4
Categorical

HIGH CARDINALITY

Distinct147
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6302 
PVG-JFK
 
49
PVG-LAX
 
34
LAX-PVG
 
26
BKK-PVG
 
20
Other values (142)
 
340
ValueCountFrequency (%) 
0630293.1%
 
PVG-JFK490.7%
 
PVG-LAX340.5%
 
LAX-PVG260.4%
 
BKK-PVG200.3%
 
JFK-PVG180.3%
 
ICN-PVG160.2%
 
PVG-SIN130.2%
 
KUL-PVG110.2%
 
FOC-PVG90.1%
 
Other values (137)2734.0%
 
2021-03-11T23:51:15.331119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique69 ?
Unique (%)1.0%
2021-03-11T23:51:15.459115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length1
Mean length1.41382366
Min length1

pref_line_y3_5
Categorical

HIGH CARDINALITY

Distinct147
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6494 
PVG
 
14
PVG-JFK
 
13
LAX-PVG
 
12
JFK-PVG
 
12
Other values (142)
 
226
ValueCountFrequency (%) 
0649495.9%
 
PVG140.2%
 
PVG-JFK130.2%
 
LAX-PVG120.2%
 
JFK-PVG120.2%
 
PVG-LAX110.2%
 
JFK50.1%
 
BKK-PVG50.1%
 
KIX-PVG50.1%
 
ORD-PVG40.1%
 
Other values (137)1962.9%
 
2021-03-11T23:51:15.600115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique93 ?
Unique (%)1.4%
2021-03-11T23:51:15.729117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length7
Median length1
Mean length1.228326687
Min length1

pref_city_y3_1
Categorical

Distinct49
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
5923 
PVG
615 
SHA
 
50
JFK
 
41
LAX
 
16
Other values (44)
 
126
ValueCountFrequency (%) 
0592387.5%
 
PVG6159.1%
 
SHA500.7%
 
JFK410.6%
 
LAX160.2%
 
SIN120.2%
 
SZX80.1%
 
TAO70.1%
 
TYN70.1%
 
WUH70.1%
 
Other values (39)851.3%
 
2021-03-11T23:51:15.863116image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique21 ?
Unique (%)0.3%
2021-03-11T23:51:15.992119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.250479988
Min length1

pref_city_y3_2
Categorical

HIGH CARDINALITY

Distinct83
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
5938 
JFK
 
193
LAX
 
151
PVG
 
143
SHA
 
33
Other values (78)
 
313
ValueCountFrequency (%) 
0593887.7%
 
JFK1932.9%
 
LAX1512.2%
 
PVG1432.1%
 
SHA330.5%
 
SIN300.4%
 
PEK140.2%
 
PUS120.2%
 
ICN110.2%
 
NKG110.2%
 
Other values (73)2353.5%
 
2021-03-11T23:51:16.130118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique29 ?
Unique (%)0.4%
2021-03-11T23:51:16.268118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.246049328
Min length1

pref_city_y3_3
Categorical

HIGH CARDINALITY

Distinct88
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6151 
JFK
 
101
LAX
 
94
PVG
 
47
ICN
 
34
Other values (83)
 
344
ValueCountFrequency (%) 
0615190.8%
 
JFK1011.5%
 
LAX941.4%
 
PVG470.7%
 
ICN340.5%
 
SHA260.4%
 
HKG210.3%
 
PEK190.3%
 
BKK180.3%
 
XIY150.2%
 
Other values (78)2453.6%
 
2021-03-11T23:51:16.408119image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique24 ?
Unique (%)0.4%
2021-03-11T23:51:16.546120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length3
Median length1
Mean length1.183133954
Min length1
Distinct46
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6254 
Shanghai
 
251
New York
 
130
Los Angeles
 
57
Beijing
 
9
Other values (41)
 
70
ValueCountFrequency (%) 
0625492.4%
 
Shanghai2513.7%
 
New York1301.9%
 
Los Angeles570.8%
 
Beijing90.1%
 
TAIPEI60.1%
 
BANGKOK40.1%
 
Nanjing3< 0.1%
 
Seoul3< 0.1%
 
Yantai3< 0.1%
 
Other values (36)510.8%
 
2021-03-11T23:51:16.705751image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique23 ?
Unique (%)0.3%
2021-03-11T23:51:16.846783image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length22
Median length1
Mean length1.554127898
Min length1
Distinct45
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6116 
Shanghai
 
400
New York
 
110
Los Angeles
 
61
Beijing
 
8
Other values (40)
 
76
ValueCountFrequency (%) 
0611690.3%
 
Shanghai4005.9%
 
New York1101.6%
 
Los Angeles610.9%
 
Beijing80.1%
 
TAIPEI60.1%
 
Fuzhou50.1%
 
BANGKOK40.1%
 
SAN FRANCISICO40.1%
 
Xi'an40.1%
 
Other values (35)530.8%
 
2021-03-11T23:51:16.976784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique21 ?
Unique (%)0.3%
2021-03-11T23:51:17.109780image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length22
Median length1
Mean length1.703588835
Min length1
Distinct40
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6087 
Shanghai
 
436
New York
 
99
Los Angeles
 
54
Beijing
 
9
Other values (35)
 
86
ValueCountFrequency (%) 
0608789.9%
 
Shanghai4366.4%
 
New York991.5%
 
Los Angeles540.8%
 
Beijing90.1%
 
TAIPEI70.1%
 
Xi'an60.1%
 
Guangzhou50.1%
 
Nanjing50.1%
 
SAN FRANCISICO40.1%
 
Other values (30)590.9%
 
2021-03-11T23:51:17.241781image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique13 ?
Unique (%)0.2%
2021-03-11T23:51:17.366785image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length22
Median length1
Mean length1.734012701
Min length1

pit_add_chnl_y3
Categorical

MISSING

Distinct3
Distinct (%)< 0.1%
Missing96
Missing (%)1.4%
Memory size52.9 KiB
0
6502 
航空累积
 
168
非航累积
 
5
ValueCountFrequency (%) 
0650296.0%
 
航空累积1682.5%
 
非航累积50.1%
 
(Missing)961.4%
 
2021-03-11T23:51:17.474782image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique0 ?
Unique (%)0.0%
2021-03-11T23:51:17.562780image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:17.651781image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length4
Median length1
Mean length1.105006646
Min length1

seat_walkway_cnt_y3
Real number (ℝ≥0)

ZEROS

Distinct30
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4339093192
Minimum0
Maximum89
Zeros6129
Zeros (%)90.5%
Memory size52.9 KiB
2021-03-11T23:51:18.014785image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum89
Range89
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.563151403
Coefficient of variation (CV)5.907113053
Kurtosis531.6123631
Mean0.4339093192
Median Absolute Deviation (MAD)0
Skewness18.98094684
Sum2938
Variance6.569745114
MonotocityNot monotonic
2021-03-11T23:51:18.137784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%) 
0612990.5%
 
11332.0%
 
21291.9%
 
31131.7%
 
4691.0%
 
5600.9%
 
6410.6%
 
7190.3%
 
8190.3%
 
9170.3%
 
Other values (20)420.6%
 
ValueCountFrequency (%) 
0612990.5%
 
11332.0%
 
21291.9%
 
31131.7%
 
4691.0%
 
ValueCountFrequency (%) 
892< 0.1%
 
581< 0.1%
 
541< 0.1%
 
481< 0.1%
 
471< 0.1%
 

seat_window_cnt_y3
Real number (ℝ≥0)

SKEWED
ZEROS

Distinct23
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2668734308
Minimum0
Maximum92
Zeros6289
Zeros (%)92.9%
Memory size52.9 KiB
2021-03-11T23:51:18.242784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum92
Range92
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.83140016
Coefficient of variation (CV)6.862429708
Kurtosis1039.551104
Mean0.2668734308
Median Absolute Deviation (MAD)0
Skewness25.06414781
Sum1807
Variance3.354026545
MonotocityNot monotonic
2021-03-11T23:51:18.350806image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%) 
0628992.9%
 
11522.2%
 
21131.7%
 
3681.0%
 
4500.7%
 
5220.3%
 
8130.2%
 
6130.2%
 
7100.1%
 
980.1%
 
Other values (13)330.5%
 
ValueCountFrequency (%) 
0628992.9%
 
11522.2%
 
21131.7%
 
3681.0%
 
4500.7%
 
ValueCountFrequency (%) 
921< 0.1%
 
481< 0.1%
 
361< 0.1%
 
241< 0.1%
 
231< 0.1%
 

seat_middle_cnt_y3
Real number (ℝ≥0)

ZEROS

Distinct12
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.1379412199
Minimum0
Maximum16
Zeros6353
Zeros (%)93.8%
Memory size52.9 KiB
2021-03-11T23:51:18.449782image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum16
Range16
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.7058693479
Coefficient of variation (CV)5.117174898
Kurtosis128.3190002
Mean0.1379412199
Median Absolute Deviation (MAD)0
Skewness9.177940107
Sum934
Variance0.4982515363
MonotocityNot monotonic
2021-03-11T23:51:18.544784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%) 
0635393.8%
 
11742.6%
 
21251.8%
 
3600.9%
 
4310.5%
 
6100.1%
 
590.1%
 
1340.1%
 
92< 0.1%
 
71< 0.1%
 
Other values (2)2< 0.1%
 
ValueCountFrequency (%) 
0635393.8%
 
11742.6%
 
21251.8%
 
3600.9%
 
4310.5%
 
ValueCountFrequency (%) 
161< 0.1%
 
1340.1%
 
92< 0.1%
 
81< 0.1%
 
71< 0.1%
 

avg_dist_cnt_y2
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct513
Distinct (%)7.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean759.1510111
Minimum0
Maximum14363.66667
Zeros6084
Zeros (%)89.9%
Memory size52.9 KiB
2021-03-11T23:51:18.673784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7075
Maximum14363.66667
Range14363.66667
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2492.929081
Coefficient of variation (CV)3.283838189
Kurtosis11.38700788
Mean759.1510111
Median Absolute Deviation (MAD)0
Skewness3.450420344
Sum5140211.496
Variance6214695.405
MonotocityNot monotonic
2021-03-11T23:51:18.813781image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0608489.9%
 
13239380.6%
 
10837.5130.2%
 
1086790.1%
 
5975.580.1%
 
1339070.1%
 
7176.2560.1%
 
13188.6666750.1%
 
1308850.1%
 
301950.1%
 
Other values (503)5918.7%
 
ValueCountFrequency (%) 
0608489.9%
 
4071< 0.1%
 
4901< 0.1%
 
490.66666671< 0.1%
 
6751< 0.1%
 
ValueCountFrequency (%) 
14363.666671< 0.1%
 
14363.52< 0.1%
 
1339070.1%
 
13314.51< 0.1%
 
13289.333331< 0.1%
 

avg_dist_cnt_y3
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct540
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean745.2562932
Minimum0
Maximum14363.66667
Zeros6086
Zeros (%)89.9%
Memory size52.9 KiB
2021-03-11T23:51:18.959414image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile7075
Maximum14363.66667
Range14363.66667
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2452.161296
Coefficient of variation (CV)3.290359731
Kurtosis11.42732767
Mean745.2562932
Median Absolute Deviation (MAD)0
Skewness3.454084287
Sum5046130.361
Variance6013095.023
MonotocityNot monotonic
2021-03-11T23:51:19.094106image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0608689.9%
 
13239230.3%
 
10837.5130.2%
 
1310390.1%
 
1296780.1%
 
301960.1%
 
7176.2560.1%
 
1086750.1%
 
13188.6666740.1%
 
1339040.1%
 
Other values (530)6079.0%
 
ValueCountFrequency (%) 
0608689.9%
 
11< 0.1%
 
4071< 0.1%
 
4901< 0.1%
 
490.66666671< 0.1%
 
ValueCountFrequency (%) 
14363.666671< 0.1%
 
14363.52< 0.1%
 
1339040.1%
 
13289.333331< 0.1%
 
13269.21< 0.1%
 

flt_cnt_y3
Categorical

HIGH CARDINALITY

Distinct91
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6027 
4
 
131
2
 
83
6
 
81
3
 
74
Other values (86)
 
375
ValueCountFrequency (%) 
0602789.0%
 
41311.9%
 
2831.2%
 
6811.2%
 
3741.1%
 
8560.8%
 
5480.7%
 
7310.5%
 
1290.4%
 
10230.3%
 
Other values (81)1882.8%
 
2021-03-11T23:51:19.249149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique55 ?
Unique (%)0.8%
2021-03-11T23:51:19.372149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length10
Median length1
Mean length1.090680845
Min length1

flt_leg_i_cnt_y3
Real number (ℝ≥0)

ZEROS

Distinct29
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.6192586029
Minimum0
Maximum67
Zeros6004
Zeros (%)88.7%
Memory size52.9 KiB
2021-03-11T23:51:19.477165image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile4
Maximum67
Range67
Interquartile range (IQR)0

Descriptive statistics

Standard deviation2.598899002
Coefficient of variation (CV)4.196791115
Kurtosis181.233607
Mean0.6192586029
Median Absolute Deviation (MAD)0
Skewness10.24146107
Sum4193
Variance6.754276023
MonotocityNot monotonic
2021-03-11T23:51:19.585145image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%) 
0600488.7%
 
41562.3%
 
21321.9%
 
3931.4%
 
1761.1%
 
6651.0%
 
5530.8%
 
8440.6%
 
7310.5%
 
9250.4%
 
Other values (19)921.4%
 
ValueCountFrequency (%) 
0600488.7%
 
1761.1%
 
21321.9%
 
3931.4%
 
41562.3%
 
ValueCountFrequency (%) 
671< 0.1%
 
612< 0.1%
 
411< 0.1%
 
322< 0.1%
 
311< 0.1%
 

flt_leg_d_cnt_y3
Categorical

Distinct40
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size52.9 KiB
0
6421 
2
 
69
1
 
69
3
 
48
4
 
32
Other values (35)
 
132
ValueCountFrequency (%) 
0642194.8%
 
2691.0%
 
1691.0%
 
3480.7%
 
4320.5%
 
{'1': 0, '2': 0, '3': 0, '4': 0, '5': 0, '6': 0}260.4%
 
5170.3%
 
6160.2%
 
7140.2%
 
990.1%
 
Other values (30)500.7%
 
2021-03-11T23:51:19.727146image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Frequencies of value counts

Unique

Unique20 ?
Unique (%)0.3%
2021-03-11T23:51:19.849149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram of lengths of the category

Length

Max length48
Median length1
Mean length1.336434795
Min length1

mdl_mcv
Real number (ℝ≥0)

ZEROS

Distinct25
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean8.064829212
Minimum0
Maximum300
Zeros6103
Zeros (%)90.1%
Memory size52.9 KiB
2021-03-11T23:51:19.952148image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile70
Maximum300
Range300
Interquartile range (IQR)0

Descriptive statistics

Standard deviation30.7266159
Coefficient of variation (CV)3.809952461
Kurtosis24.75570153
Mean8.064829212
Median Absolute Deviation (MAD)0
Skewness4.70023363
Sum54606.95859
Variance944.1249249
MonotocityNot monotonic
2021-03-11T23:51:20.058149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%) 
0610390.1%
 
201231.8%
 
50661.0%
 
40550.8%
 
120550.8%
 
70420.6%
 
130320.5%
 
100320.5%
 
10310.5%
 
140270.4%
 
Other values (15)2053.0%
 
ValueCountFrequency (%) 
0610390.1%
 
10310.5%
 
201231.8%
 
28.1956791< 0.1%
 
29.381457292< 0.1%
 
ValueCountFrequency (%) 
30040.1%
 
250110.2%
 
220110.2%
 
21050.1%
 
20080.1%
 

tkt_avg_amt_y1
Real number (ℝ≥0)

ZEROS

Distinct461
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean102.2141837
Minimum0
Maximum13654.92
Zeros6266
Zeros (%)92.5%
Memory size52.9 KiB
2021-03-11T23:51:20.179149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile417.9521428
Maximum13654.92
Range13654.92
Interquartile range (IQR)0

Descriptive statistics

Standard deviation591.2974563
Coefficient of variation (CV)5.78488655
Kurtosis137.4922901
Mean102.2141837
Median Absolute Deviation (MAD)0
Skewness10.03331538
Sum692092.2376
Variance349632.6818
MonotocityNot monotonic
2021-03-11T23:51:20.310149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0626692.5%
 
2493.6553< 0.1%
 
850.473753< 0.1%
 
5320.2036843< 0.1%
 
1121.2894743< 0.1%
 
257.40111113< 0.1%
 
213.061252< 0.1%
 
733.2852< 0.1%
 
520.62< 0.1%
 
3336.2952< 0.1%
 
Other values (451)4827.1%
 
ValueCountFrequency (%) 
0626692.5%
 
0.00251< 0.1%
 
14.5851< 0.1%
 
15.0641< 0.1%
 
15.111707321< 0.1%
 
ValueCountFrequency (%) 
13654.921< 0.1%
 
11712.676671< 0.1%
 
9937.4151< 0.1%
 
9079.4551< 0.1%
 
9020.441< 0.1%
 

tkt_avg_amt_y2
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct593
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean182.3033287
Minimum0
Maximum21898.53
Zeros6128
Zeros (%)90.5%
Memory size52.9 KiB
2021-03-11T23:51:20.450149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile995.95875
Maximum21898.53
Range21898.53
Interquartile range (IQR)0

Descriptive statistics

Standard deviation920.5085624
Coefficient of variation (CV)5.049323943
Kurtosis120.6585729
Mean182.3033287
Median Absolute Deviation (MAD)0
Skewness9.176780875
Sum1234375.838
Variance847336.0134
MonotocityNot monotonic
2021-03-11T23:51:20.576149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0612890.5%
 
2267.4557893< 0.1%
 
1589.50253< 0.1%
 
2790.3833333< 0.1%
 
636.30888893< 0.1%
 
5320.2036843< 0.1%
 
1249.0992< 0.1%
 
830.63752< 0.1%
 
2579.44952< 0.1%
 
525.3522< 0.1%
 
Other values (583)6209.2%
 
ValueCountFrequency (%) 
0612890.5%
 
15.0641< 0.1%
 
25.541< 0.1%
 
43.46751< 0.1%
 
72.5751< 0.1%
 
ValueCountFrequency (%) 
21898.531< 0.1%
 
16115.703331< 0.1%
 
14113.381< 0.1%
 
13654.921< 0.1%
 
13598.8051< 0.1%
 

tkt_avg_amt_y3
Real number (ℝ≥0)

HIGH CORRELATION
ZEROS

Distinct618
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean208.1421056
Minimum0
Maximum21898.53
Zeros6102
Zeros (%)90.1%
Memory size52.9 KiB
2021-03-11T23:51:20.711149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1129.823333
Maximum21898.53
Range21898.53
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1012.999276
Coefficient of variation (CV)4.866863785
Kurtosis99.24700009
Mean208.1421056
Median Absolute Deviation (MAD)0
Skewness8.509208362
Sum1409330.197
Variance1026167.533
MonotocityNot monotonic
2021-03-11T23:51:20.840149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%) 
0610290.1%
 
5320.2036843< 0.1%
 
686.38277783< 0.1%
 
2790.3833333< 0.1%
 
1773.833< 0.1%
 
3489.6268423< 0.1%
 
2158.4444442< 0.1%
 
936.28833332< 0.1%
 
1257.782< 0.1%
 
826.5452< 0.1%
 
Other values (608)6469.5%
 
ValueCountFrequency (%) 
0610290.1%
 
15.0641< 0.1%
 
43.46751< 0.1%
 
56.951< 0.1%
 
107.2781< 0.1%
 
ValueCountFrequency (%) 
21898.531< 0.1%
 
16115.703331< 0.1%
 
14113.381< 0.1%
 
13862.9751< 0.1%
 
13654.921< 0.1%
 

Interactions

2021-03-11T23:50:54.056022image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:54.232997image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:54.336115image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:54.454117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:54.581112image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:54.699117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:54.816120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.024114image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.159117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.267117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.370117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.471117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.572118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.692118image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.808229image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:55.926229image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.034233image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.146563image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.256538image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.358538image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.471535image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.603535image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.726538image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.855538image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:56.977538image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.101739image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.223899image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.344965image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.469963image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.585964image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.702556image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.815124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:57.948124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.089125image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.225120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.363124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.499124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.628123image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.758124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.876123image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:58.997120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:59.115120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:59.229120image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:59.471122image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:59.609124image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:59.747798image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:50:59.879373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.004373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.144372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.270372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.386372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.500368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.621371image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.755373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:00.888372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.019372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.151373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.274368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.400373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.524372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.650372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.775369image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:01.898373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.021373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.140372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.256371image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.372370image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.485368image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.604369image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.717371image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.829372image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:02.947384image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.070374image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.212373image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.347710image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.471784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.591784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.711780image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.843784image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:03.966780image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:04.085781image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:04.199455image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:04.318085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:04.445085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:04.565086image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:04.683082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:04.800086image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.053086image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.185085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.300086image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.412082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.518085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.622103image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.734117image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.846081image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:05.960085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:06.070085image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:06.177086image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:06.292082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:06.398082image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Correlations

2021-03-11T23:51:20.965149image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-03-11T23:51:21.177675image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-03-11T23:51:21.380380image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-03-11T23:51:21.630691image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.
2021-03-11T23:51:22.003455image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-03-11T23:51:06.850998image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:08.347261image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/
2021-03-11T23:51:08.853539image/svg+xmlMatplotlib v3.3.3, https://matplotlib.org/

Sample

First rows

pax_namepax_passportseg_route_toseg_flightseg_cabinemd_lableemd_lable2genderageresidence_countrynation_nameprovince_namemember_levelenroll_chnlpref_aircraft_m3_1pref_aircraft_m3_2pref_aircraft_y3_1pref_aircraft_y3_2pref_aircraft_y3_3pref_aircraft_y3_4pref_aircraft_y3_5pref_line_y3_1pref_line_y3_2pref_line_y3_3pref_line_y3_4pref_line_y3_5pref_city_y3_1pref_city_y3_2pref_city_y3_3pref_dest_city_y1pref_dest_city_y2pref_dest_city_y3pit_add_chnl_y3seat_walkway_cnt_y3seat_window_cnt_y3seat_middle_cnt_y3avg_dist_cnt_y2avg_dist_cnt_y3flt_cnt_y3flt_leg_i_cnt_y3flt_leg_d_cnt_y3mdl_mcvtkt_avg_amt_y1tkt_avg_amt_y2tkt_avg_amt_y3
021f0b1c838160ac26cb2c57660bc3fd583685748783343bccba7a8c3c6a5c813JFKAB1010Y00051-600美国SHSTD其它0000000CAN-SHAYVR-PVGSHA-CANPVG-JFKPVG-YVR000New YorkShanghaiShanghai00108636.85658.9230771307130.0282.256923524.7500920.134615
121e0621a85f6db6139ff7cf2d53b4e5d38da646d04551c8ad4652ab9d8a944b0LAXAB1008Y00000000000000000000000000000000.00.0000000000.00.0000000.00000.000000
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Last rows

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Duplicate rows

Most frequent

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